Associations between the Brief Memory and Executive Test (BMET), Activities of Daily Living, and Quality of Life in Patients with Cerebral Small Vessel Disease
Bibliographic record
Abstract
OBJECTIVES: In addition to neuropsychological difficulties, patients with cerebral small vessel disease (SVD) can have reduced activities of daily living and a poorer quality of life compared to healthy adults. The Brief Memory and Executive Test (BMET), is a cognitive screening tool designed to be sensitive to the neuropsychological profile of patients with SVD. While the BMET is sensitive to the cognitive consequences of SVD, it is unclear how well scores on this measure relate to functional outcomes. The aims of this study are to investigate the relationship between scores on the BMET and functional outcomes (activities of daily living and quality of life) in SVD, and to compare this with other commonly used cognitive screening tools. METHODS: This study included 184 participants with SVD (mean age=63.2; SD=9.9) and 299 healthy controls (mean age=62.4; SD=13.8) who were tested using the BMET, Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Stroke Specific - Quality of Life Scale (SS-QoL), Geriatric Depression Scale (GDS), and measures of both instrumental activities of daily living (IADL) and basic activities of daily living (BADL). RESULTS: After controlling for covariates the scores on the BMET, but not the MoCA or MMSE, were significantly related to poorer IADL and quality of life in the SVD group. In addition to the BMET scores, symptoms of depression were found to be significant associated with functional outcome. CONCLUSION: These results support the clinical utility of using of the BMET, in combination with a standardized depression questionnaire, during the early assessment of patients with SVD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".